Given the proliferation of use of the Internet, there is a need to build an interface between a genetic algorithm and the Internet. A genetic algorithm is a randomized parallel search algorithm that searches from a population of points normally consisting of a bit string encoded to represent the data or individuals of a population. The genetic algorithm proceeds by evaluating and modifying the strings utilizing genetic operators such as selection, crossover, and mutation. The conventional genetic algorithm uses a bit string to encode the individuals in its population. As a result, the amount and complexity of the data that can be encoded is limited. It also means that the individual of a population, which comprises the solution of the problem, is not human readable. The individual needs to be translated back into a solution understandable by the user. This means that the genetic algorithm is a “black box” and is an intermediate solution not human readable. Thus, there is a need for an improved interface between a genetic algorithm and the Internet.